"Hey Claude, what's the total from this file?
> grep for headers
> "Ah, I see column 3 is the price value"
> SUM(C2:C) -> $2020
> "Great! I found your total!"
If you can find me an example of tech that can solve this at scale on large, diverse Excel formats, then I'll concede, but I haven't found something actually trustworthy for important data sets
IMO, a real solution here has to be hybrid, not full LLM, because these sheets can be massive and have very complicated structures. You want to be able to use the LLM to identify / map column headers, while using non-LLM tool calling to run Excel operations like SUMIFs or VLOOKUPs. One of the most important traits in these systems is consistency with slight variation in file layout, as so much Excel work involves consolidating / reconciling between reports made on a quarterly basis or produced by a variety of sources, with different reporting structures.
Disclosure: My company builds ingestion pipelines for large multi-tab Excel files, PDFs, and CSVs.
Danya was like the Mr. Rogers of chess. He had a way of making you feel accepted into the chess community even if you were a beginner, and was such a clear thinker. I strive to be more like him, and am devastated by this loss.
Syncopate | NYC (Hybrid ~3d/week) | Full-time | Senior Full Stack Engineers / Focus on AI + Finance
Syncopate builds tools to help automate financial diligence and management of long-tail financial assets.
We've found product market fit with ETL/analysis tools for niche financial data, starting with music rights, and we're looking to build out our capabilities across more Excel + PDF-based workflows.
What we're looking for: A full-stack engineer with experience building data-heavy applications. Experience with analytics databases like Clickhouse and data pipelining is a plus. Required to be knowledgeable in Typescript.
Big bonus points for:
1) High agency (previously a founder or built side-projects to completion)
2) Some knowledge of finance
3) Skill in Rust